The present invention relates to information processing systems for large or massive information networks, such as the internet, and more particuarly to such information systems in which an information filter structure uses collaborative feedback data in determining the value of a document or other information entity (informon) to a user.
In the operation of the internet, a countless number of informons are available for downloading from any of at least thousands of sites for consideration by a user at the user's location. A user typicaly connects to a portal or other web site having a search capability, and thereafter enters a particular query, i.e., a request for informons relevant to a topic, a field of interest, etc. Thereafter, the search site typically employs a "spider" scanning system and a content-based filter in a search engine to search the internet for informons which match the query. This process is basically a pre-search process in which matching informons are found, at the time of initiating the search for the user's query. by comparing informons in an "informon data base" to the user's query.
The return list of matching informons can be very extensive according to the subject of the query and the breadth of the query. More specific queries typically result in shorter return lists. In some cases, the search site may also be structured to find web sites which probably have stored informons matching the entered query.
Collaborative data can be made available to assist in informon rating when a user actually downloads an informon, considers and evaluates it, and returns data to the search site as a representation of the value of the considered informon to the user.
In the patent application parent to this divisional application, i.e., Ser. No. 08/627,436, now U.S. Pat. No. 5,867,799, filed by the present inventors on Apr. 4, 1996, and hereby incorporated by reference, an advanced collaborative/content-based information filter system is employed to provide superior fitering in the process of finding and rating informons which match a user's query. The information filter structure in this system integrates content-based filtering and collaborative filtering to determine relevancy of informons received from various sites in the internet or other network. In operation, an individual user enters a query and a corresponding "wire" is established, i.e., the query is profiled in storage on a content basis and adaptively updated over time, and informons obtained from the network are compared to the profile for relevancy and ranking. A continuously operating "spider" scans the network to find informons which are received and processed for relevancy to the individual user's wire and for relevancy to wires established by numerous other users.
The integrated filter system compares received informons to the individual user's query profile data, combined with collaborative data, and ranks, in order of value, informons found to be relevant. The system maintains the ranked informons in a stored list from which the individual user can select any listed informon for consideration.
As the system continues to operate the individual user's wire, the stored relevant informon list typically changes due to factors including a return of new and more relevant informons, adjustments in the user's query, feedback evaluations by the user for considered informons, and updatings in collaborative feedback data. Received informons are similarly processed for other users' wires established in the information filter system. Thus, the integrated information filter system compares network informons to multiple user's queries to find matching informons for various users' wires over the course of time, whereas conventional search engines initiate a search in response to an individual user's query and use content-based filtering to compare the query to accessed network informons to find matching informons during a limited search time period.
The present invention is directed to an informon rating system in which content-based filter profile data and collaborative feedback filter data are integrated and compared to data representative of an informon being rated to determine the relevancy and value of the informon to an individual user. This system is embodied in the multi-level, integrated collaborative/content-based filter disclosed in the parent application, and it receives informon data, which is passed downwardly through the filter structure, and collaborative feedback data which is sent from a collaborative feedback data processsing system called a mindpool system. Another copending patent application, entitled MULTI-LEVEL MINDPOOL SYSTEM ESPECIALLY ADAPTED TO PROVIDE COLLABORATIVE FILTER DATA FOR A LARGE-SCALE INFORMATION FILTERING SYSTEM, Serial Number (Atty. docket # LYC2), filed by the current inventors concurrenty herewith, provides further discosure and explanation of the mindpool system.